REA model is an approach to conceptualizing the semantic of economics exchange such as accounting transaction. It is set as an ISO standard (ISO / IEC 15944-4:2007) to develop a resource, events, agents model of an accounting system. It was developed in late 1982 by William E. McCarthy as a generalized accounting model. It is used to provide crucial information associates with business policies and activities. Apparently, people seem to use the model for various reason such as capturing information associate with the value creation patterns, describing database and so on.
Amazon travel Club Case Study:
Amazon travel club is a retailer, markets travel books across North America region. Usually, customers ordered through their website. However they can also book an order by email or phones. All authenticated orders are stored into Amazon travel Club’s computer system by their sales representatives.
Amazon Travel Club follows a systemic approach from booking to shipping as follows;
The rea diagram will be constructed with the information described above. The rea data model will focus on amazon’s revenue and expenditure cycle to show the business process effectively.
REA accounting data model of revenue cycle:
REA model is basically used for design a database management system. It assist to recognize the interconnection between the revenue, events and agents by structuring the relations among entities (Romney and Steinbart 2013). In REA model: Resources are goods or services which has some economic value. Events specifies some business events such as transaction and finally the agents are stakeholder associates with the events such as employees and customers.
Revenue Style
In order to create an entity-relationship diagram with the help of the REA model, there would be three steps that need to be involved as follows:
Identify resources and agents:
In the amazon travel Shop system there are mainly two resources identified as inventory and cash. There are also several events identified from the case study as sales representative who are responsible for enter order information into their database. Another agents is shipping clerk who is responsible for the retrieving the orders from the inventory and ship them. Purchasing agents are responsible for purchase order to the vendor (Ito and Vym?ta 2016). Receiving clerk is responsible for putting the items into the inventory and disbursement clerk pays all vendor invoices. Suppliers are responsible for supplying order items. And as usual customer orders the items.
Events:
.customer .sales representative
.shipping clerk .customer
Determination of the Cardinalities of Relationships
This is the final step in the drawing of an REA diagram. The cardinalities would be able to define the number of sales transactions that could be associated with each of the customers and vice-versa. The REA model could be documented in the same form as an entity-relationship (E-R) diagram.
Minimum Cardinality – In this type of cardinality, it could be either zero (0) or one (1), which would depend on the entity based relationship.
Maximum Cardinality – In this type of cardinality, it could be either many or one. This could be represented by “crow’s feet”. This would depend on the fact that whether each of the instances of the entity A could be linked with any of the instances of the entity B.
Since the maximum cardinality is many, hence it would represent that a particular customer might be involved with several transactions. There are three kinds of relationships that would depend on the maximum cardinalities, such as:
Each organization would have their own model of REA that would reflect the information about the practices of business, which would be obtained from the analysis of various systems and stages of conceptual based design (Gailly and Geerts 2013).
Agent-Event Relationship Cardinalities
Each of the event should be linked to an individual. The minimum cardinality on the side of an individual should be one, whereas the minimum cardinality that would be associated with the event side of the relationship based on the events of the agents should be 0. The various cardinalities that would be associated with each of the individual agent should have 0 minimums and N number of maximums.
There are two major reasons about the fact that the minimum cardinalities within the agent-event relationship is majorly 0. Initially, the information about the potential based customer and supplier should be added that would have not been taken in any of the kind of transactions. In the second process, it should be taken into account that the entities of the agent should be equivalent to the files of the master. At the initiation of the fiscal year, the account of the customers might not be linked with any of the event of the present value of sales.
Resource-Event Relationship Cardinalities
The minimum and maximum cardinalities that should be associated with each of the resource in the relationships based on resource-events are 0 and N respectively. This kind of relationship would mostly be common for such kind of similar organizations for most of their usage of resources. If any organization would sell one kind of inventory, the maximum cardinality on the side of events would be 1. This would be done due to the reason that organizations would be wishing to sell more of those kind of items. Hence the maximum cardinality on the side of inventory should be many.
Specific Event-Resource Relationship Cardinalities
Each of the order should be able to involve at least one of the items of the inventory but that could also be for many different items (Casu et al. 2016). In a similar manner, each of the delivery of the merchandise product should involve at least one of the items form the inventory. They might also include many other different kind of items. Accordingly, Amazon would depict the minimum cardinality as 1 and the value of the maximum cardinality as N on the side of the inventory based on every relationships between the various events and the resource of inventory.
The information of the inventory would be maintained in an indefinite manner. The orders and the receipts of the inventory that had occurred previously during the present fiscal year should be properly maintained within the database (Chamorro et al. 2016). Hence, at the starting of each of the inventory year, the entity of the inventory should not be linked to any other form of order or they should not receive any of the events of the inventory.
Expenditure Cycle
An expenditure cycle is a generalize from of the purchasing decisions and actions. It is the repetitive process of generating purchase orders and ordering services and goods. It also include the invoices for the items and services.
The steps for constructing the REA model is followed;
Step 1. Identify Events;
The first step is to identify the events while using “give to get” exchange. After analyzing the business process of the amazon travel club some events are identified which are followed:
Step 2: identification of agents and resources
There are only two resources identified associates with the events as inventory and cash.
. Sales perspective .supplier
.receiving clerk .supplier
. supplier .disbursement clerk
Relational Database Model
Once the diagram of REA has been developed, it could be used in order to design a well-structured relational database. The REA model is extremely important for understanding of the similar form of entities and the various differences within the policies of the business (Bimonte et al. 2013). This would result in differentiating between the relationships within the cardinalities.
Entity |
Primary Key |
Foreign key |
Other Attributes |
Sales Representative |
S.R_ID |
Name, DOB, Date Hired, Pay rate, Job Title |
|
Customers |
Customer_ID |
Name, DOB, Address, |
|
Suppliers |
Supplier_ID |
Name, Address, Performance rating |
|
Order Inventory |
Order_number |
Supplier_ID, Customer_ID |
Order quantity, Cost, date |
Received Inventory |
Inventor_ID |
Supplier_ID, Customer_ID, Order_ID |
Quantity Received, date, |
Cash |
Account_number |
Type of account, Date, Account holder name. |
|
sales |
Invoice_number |
Supplier_ID, Customer_ID, Order_ID |
Date time, invoice Sent |
disbursement clerk |
Dclerk_ID |
Name, Address, Performance rating, payment rate |
|
Shipping Clerk |
Sclerk_ID |
Name, Address, Performance rating, payment rate |
Summary and Conclusion:
The data base designing process can be divided into five different stages namely the system analysis, the physical designing, operation maintenance and implementation and conversion. In case of the accountants, it has become a necessity to learn all these designing processes in order to do a work in a perfect manner. According to many of the researchers, one of the best ways that can be used for this purpose is to perform activities of system analysis in order to build a better data model of the AIS system. The Revenue entity agent accounting model is developed in a specifically designing a database model of the AIS.
Further the Accounting Entity model classifies the objects in three different sub categories namely the resources, the events and the agents. Further the REA can be documented in an entity relationship model diagram in order to provide more details. These model can be used for the purpose of the showing the amount of the data that are collected represented by rectangles and relationships depicted by connecting lines.
As per the entity relationship model the cardinalities of the relationship that are depicted in the REA that is the Revenue Entity Agent model specifies the minimum number of times on which a single entity can be linked with another entity that is present in the diagram. These diagrams can also be sued for the purpose of gaining information about the business polies that an organization follows.
Developing a REA diagram is a three step process, the first basic step is to understanding the events of the interest that is any activity which the management wants to collect proper information, evaluate the information and evaluate the performance.
The second step of the task is properly identify the resources that are affected by the agents who are participating in the events. The third step is to properly use the information about the organizations business practices and the add relationships. These are some of the most useful things that are to be done in order to get a proper entity model working, these were some of the steps that were followed by John for the process of the developing REA diagram for Fred’s Busses shop revenue cycle. Further John explained each and every aspect of the model to the client and when the client approved that every aspect of the model was totally correct. Hence John explained that he will proceed with this model to create the relational database.
Reference:
Bimonte, S., Barbieri, A., Palma, G., Luciano, A., Rea, D. and Arra, C., 2013. Curcumin inhibits tumor growth and angiogenesis in an orthotopic mouse model of human pancreatic cancer. BioMed research international, 2013.
Casu, C., Aghajan, M., Oikonomidou, P.R., Guo, S., Monia, B.P. and Rivella, S., 2016. Combination of Tmprss6-ASO and the iron chelator deferiprone improves erythropoiesis and reduces iron overload in a mouse model of beta-thalassemia intermedia. Haematologica, 101(1), pp.e8-e11.
Chamorro, L.P., Hill, C., Morton, S., Ellis, C., Arndt, R.E.A. and Sotiropoulos, F., 2013. On the interaction between a turbulent open channel flow and an axial-flow turbine. Journal of Fluid Mechanics, 716, pp.658-670.
Gailly, F. and Geerts, G.L., 2013. Formal definition of business rules using REA business modeling language. In 7th International Workshop on Value Modeling and Business Ontology (VMBO 2013), Proceedings.
Ito, S. and Vym?tal, D., 2013. The formal REA model at the operational level. Applied Ontology, 8(4), pp.275-300.
Mondragón, R., Juliá, J.E., Hernández, L. and Jarque, J.C., 2013. Modeling of drying curves of silica nanofluid droplets dried in an acoustic levitator using the Reaction Engineering Approach (REA) model. Drying technology, 31(4), pp.439-451.
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Perez?Polo, J.R., Rea, H.C., Johnson, K.M., Parsley, M.A., Unabia, G.C., Xu, G.Y., Prough, D., DeWitt, D.S., Spratt, H. and Hulsebosch, C.E., 2015. A rodent model of mild traumatic brain blast injury. Journal of neuroscience research, 93(4), pp.549-561.
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